Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö B
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
ÈÞ¸®½ºÆ½¿¡ ÀÇÇÏ¿© °³¼±µÈ ¹Ýµ÷ºÒÀÌ ¾Ë°í¸®ÁòÀÇ ¼³°è¿Í ºÐ¼® |
¿µ¹®Á¦¸ñ(English Title) |
A Design and Analysis of Improved Firefly Algorithm Based on the Heuristic |
ÀúÀÚ(Author) |
ÀÌÇö¼÷
ÀÌÁ¤¿ì
¿À°æȯ
Hyunsook Rhee
Jungwoo Lee
Kyungwhan Oh
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 18-B NO. 01 PP. 0039 ~ 0044 (2011. 02) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®¿¡¼´Â ÃÖ±Ù Xin-She Yang¿¡ ÀÇÇØ ¼Ò°³µÈ ¹Ýµ÷ºÒÀÌ ¾Ë°í¸®Áò(FA)¿¡ ÈÞ¸®½ºÆ½À» Àû¿ëÇÏ¿© °³¼±ÇÏ´Â ¹æ¾ÈÀ» Á¦¾ÈÇÑ´Ù. ¶ÇÇÑ À̸¦ À§ÇÏ¿© ±âÁ¸ÀÇ FA¸¦ ÀÌ¿Í À¯»çÇÑ ¹®Á¦¿µ¿ªÀÇ ¾Ë°í¸®ÁòÀÎ Particle Swarm Optimization(PSO)¿Í Á¤È®µµ Ãø¸é, ¼ö·Å ½Ã°£ Ãø¸é, °¢ ÀÔÀÚÀÇ ¿òÁ÷ÀÓ Ãø¸é¿¡¼ ºñ±³ ºÐ¼®ÇÑ´Ù. ºñ±³ ½ÇÇè °á°ú, FAÀÇ Á¤È®µµ´Â PSOº¸´Ù ³ª»ÚÁö ¾Ê¾ÒÁö¸¸, ¼ö·Å ¼Óµµ´Â ´À¸° °ÍÀ¸·Î ³ªÅ¸³µ´Ù. º» ³í¹®Àº ÀÌ¿¡ ´ëÇÑ Á÷°üÀûÀÎ ¿øÀÎÀ» °íÂûÇÏ°í, À̸¦ ±Øº¹Çϱâ À§ÇØ, ±âÁ¸ÀÇ FA¿¡ ºÎºÐ µ¹¿¬º¯ÀÌ ÈÞ¸®½ºÆ½À» Àû¿ëÇÏ¿© °³¼±µÈ FA(Improved FA)¸¦ Á¦¾ÈÇÑ´Ù. º¥Ä¡¸¶Å© ÇÔ¼öµéÀ» ÃÖÀûÈ ÇÏ´Â ºñ±³ ½ÇÇè °á°ú, °³¼±µÈ FA°¡ PSO¿Í ±âÁ¸ÀÇ FAº¸´Ù Á¤È®µµ¿Í ¼ö·Å¼Óµµ Ãø¸é¿¡¼ ¿ì¼öÇÔÀ» º¸ÀÌ°íÀÚ ÇÑ´Ù.
|
¿µ¹®³»¿ë (English Abstract) |
In this paper, we propose a method to improve the Firefly Algorithm(FA) introduced by Xin-She Yang, recently. We design and analyze the improved firefly algorithm based on the heuristic. We compare the FA with the Particle Swarm Optimization (PSO) which the problem domain is similar with the FA in terms of accuracy, algorithm convergence time, the motion of each particle. The compare experiments show that the accuracy of FA is not worse than PSO¡¯s, but the convergence time of FA is slower than PSO¡¯s. In this paper, we consider intuitive reasons of slow convergence time problem of FA, and propose the improved version of FA using a partial mutation heuristic based on the consideration. The experiments using benchmark functions show the accuracy and convergence time of the improved FA are better than them of PSO and original FA.
|
Å°¿öµå(Keyword) |
¹Ýµ÷ºÒÀÌ ¾Ë°í¸®Áò
ÀÔÀÚ±ºÁý ÃÖÀûÈ
ºÎºÐ µ¹¿¬º¯ÀÌ
ÀÚ¿¬°è±â¹ÝÀÇ È®·üÀû ÃÖÀûÈ
Firefly Algorithm
Particle Swarm Optimization
Partial Mutation
Nature-inspired Stochastic Optimization
|
ÆÄÀÏ÷ºÎ |
PDF ´Ù¿î·Îµå
|